---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-panx-de-1
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: xtreme
      type: xtreme
      config: PAN-X.de
      split: validation
      args: PAN-X.de
    metrics:
    - name: F1
      type: f1
      value: 0.8709714026327735
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# xlm-roberta-base-finetuned-panx-de-1

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1707
- F1: 0.8710

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 132  | 0.1593          | 0.8122 |
| No log        | 2.0   | 264  | 0.1484          | 0.8427 |
| No log        | 3.0   | 396  | 0.1399          | 0.8508 |
| 0.1703        | 4.0   | 528  | 0.1395          | 0.8560 |
| 0.1703        | 5.0   | 660  | 0.1409          | 0.8562 |
| 0.1703        | 6.0   | 792  | 0.1523          | 0.8648 |
| 0.1703        | 7.0   | 924  | 0.1554          | 0.8660 |
| 0.0448        | 8.0   | 1056 | 0.1633          | 0.8681 |
| 0.0448        | 9.0   | 1188 | 0.1664          | 0.8678 |
| 0.0448        | 10.0  | 1320 | 0.1707          | 0.8710 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2